Large Language Models – Survey Results Inpher polled our community of customers, partners, and innovators to get their feedback on the usability and challenges of LLMs in their environments.
SecurAI – How it Works Discover the power of running a large language model within a Trusted Execution Environment that preserves the privacy and security of user inputs.
Solution Briefs/One Pagers
New Approaches to Tackling Financial Crimes: Secure Data Collaboration With XOR This solution brief presents four case studies that illustrate how institutions that leverage Inpher can more effectively identify and combat financial crime.
Better Together: Next Generation ESG Reporting Capabilities with Inpher’s XOR Platform & Oracle Cloud EPM Oracle Cloud EPM and Inpher XOR Platform provide a comprehensive solution that allows you to securely plan, manage, and report on your ESG practices.
Build Better Models with Sensitive Data Learn more about Inpher’s technologies and capabilities that enable our corporate and government partners to develop their data-driven platforms based on customer consent, privacy and trust.
SecurAI Leverage LLMs and generative AI privately, securely and with complete autonomy.
Balancing Privacy: Leveraging Privacy Budgets for Privacy-Enhancing Technologies Get valuable insights into privacy budget, a critical (and sometimes overlooked) aspect in ensuring robust privacy preservation in any given PETs project.
Inpher SecurAI: Enhancing Large Language Model Inference with Confidential Computing In this paper, we look at the advantages of using generative AI ethically and responsibly by leveraging Trusted Execution Environments (TEEs) and Inpher SecurAI.